Dynamic modelling and forecasting of interest rates: evidence from Scandinavian countries

Purpose Using unique data of three Scandinavian countries (Denmark, Norway and Sweden), the study examines the term structure of their interest rates and the performance of the Babbs and Nowman model in forecasting the rates covering their economic stability and financial crisis periods from 2000 to 2014. Design/methodology/approach The continuous-time multi-factor model developed by Babb’s and Nowman (1999) is employed for the research alongside the state-space form (TSIR) of the model. The linear Kalman filter algorithm is further implemented to produce the estimates for both the observable and unobservable variables. The dataset used in the study enables a critical assessment of the in-sample and out-of-sample performance across three versions of the multi-factor Babbs and Nowman model. Findings The research shows that the complexity of the three-factor model is necessary to better explain the yield curve dynamics in the case of Denmark and Norway, while for Sweden there is no clear benefit in adding a third factor. However, under the best predictive specification, the out-of-sample analysis produced different results for each country. The findings further exhibit that when considering the forecasting errors, the continuous-time models generate superior forecasts, a feature of great interest in pricing interest rate derivatives and hedging strategies. Research limitations/implications The study's empirical findings provide insights to investors, forecasters and central banks on the BN model attributes and its ability to explain the yield curve dynamics in times of economic stability and in financial crisis. Originality/value The research presents new insights on the BN multi-factor model applications on forecasting interest rates and draws on unique data of three Scandinavian countries (Denmark, Norway and Sweden). The study also provides a full spectrum of the model with application to the financial crisis period and for the post-crisis era.